11,176 research outputs found
Polynomial Curve Slope Compensation for Peak-Current-Mode-Controlled Power Converters
Linear ramp slope compensation (LRC) and quadratic slope compensation (QSC) are commonly implemented in peak-current-mode-controlled dc-dc converters in order to minimize subharmonic and chaotic oscillations. Both compensating schemes rely on the linearized state-space averaged model (LSSA) of the converter. The LSSA ignores the impact that switching actions have on the stability of converters. In order to include switching events, the nonlinear analysis method based on the Monodromy matrix was introduced to describe a complete-cycle stability. Analyses on analog-controlled dc-dc converters applying this method show that system stability is strongly dependent on the change of the derivative of the slope at the time of switching instant. However, in a mixed-signal-controlled system, the digitalization effect contributes differently to system stability. This paper shows a full complete-cycle stability analysis using this nonlinear analysis method, which is applied to a mixed-signal-controlled converter. Through this analysis, a generalized equation is derived that reveals for the first time the real boundary stability limits for LRC and QSC. Furthermore, this generalized equation allows the design of a new compensating scheme, which is able to increase system stability. The proposed scheme is called polynomial curve slope compensation (PCSC) and it is demonstrated that PCSC increases the stable margin by 30% compared to LRC and 20% to QSC. This outcome is proved experimentally by using an interleaved dc-dc converter that is built for this work
Nonlinear Analysis and Control of Interleaved Boost Converter Using Real-Time Cycle to Cycle Variable Slope Compensation
Switched-mode power converters are inherently nonlinear and piecewise smooth systems that may exhibit a series of undesirable operations that can greatly reduce the converter's efficiency and lifetime. This paper presents a nonlinear analysis technique to investigate the influence of system parameters on the stability of interleaved boost converters. In this approach, Monodromy matrix that contains all the comprehensive information of converter parameters and control loop can be employed to fully reveal and understand the inherent nonlinear dynamics of interleaved boost converters, including the interaction effect of switching operation. Thereby not only the boundary conditions but also the relationship between stability margin and the parameters given can be intuitively studied by the eigenvalues of this matrix. Furthermore, by employing the knowledge gained from this analysis, a real-Time cycle to cycle variable slope compensation method is proposed to guarantee a satisfactory performance of the converter with an extended range of stable operation. Outcomes show that systems can regain stability by applying the proposed method within a few time periods of switching cycles. The numerical and analytical results validate the theoretical analysis, and experimental results verify the effectiveness of the proposed approach
The Effect of Macrodiversity on the Performance of Maximal Ratio Combining in Flat Rayleigh Fading
The performance of maximal ratio combining (MRC) in Rayleigh channels with
co-channel interference (CCI) is well-known for receive arrays which are
co-located. Recent work in network MIMO, edge-excited cells and base station
collaboration is increasing interest in macrodiversity systems. Hence, in this
paper we consider the effect of macrodiversity on MRC performance in Rayleigh
fading channels with CCI. We consider the uncoded symbol error rate (SER) as
our performance measure of interest and investigate how different
macrodiversity power profiles affect SER performance. This is the first
analytical work in this area. We derive approximate and exact symbol error rate
results for M-QAM/BPSK modulations and use the analysis to provide a simple
power metric. Numerical results, verified by simulations, are used in
conjunction with the analysis to gain insight into the effects of the link
powers on performance.Comment: 10 pages, 5 figures; IEEE Transaction of Communication, 2012
Corrected typo
Efficient Computation of Sensitivity Coefficients of Node Voltages and Line Currents in Unbalanced Radial Electrical Distribution Networks
The problem of optimal control of power distribution systems is becoming
increasingly compelling due to the progressive penetration of distributed
energy resources in this specific layer of the electrical infrastructure.
Distribution systems are, indeed, experiencing significant changes in terms of
operation philosophies that are often based on optimal control strategies
relying on the computation of linearized dependencies between controlled (e.g.
voltages, frequency in case of islanding operation) and control variables (e.g.
power injections, transformers tap positions). As the implementation of these
strategies in real-time controllers imposes stringent time constraints, the
derivation of analytical dependency between controlled and control variables
becomes a non-trivial task to be solved. With reference to optimal voltage and
power flow controls, this paper aims at providing an analytical derivation of
node voltage and line current flows as a function of the nodal power injections
and transformers tap-changers positions. Compared to other approaches presented
in the literature, the one proposed here is based on the use of the [Y]
compound matrix of a generic multi-phase radial unbalanced network. In order to
estimate the computational benefits of the proposed approach, the relevant
improvements are also quantified versus traditional methods. The validation of
the proposed method is carried out by using both IEEE 13 and 34 node test
feeders. The paper finally shows the use of the proposed method for the problem
of optimal voltage control applied to the IEEE 34 node test feeder.Comment: accepted for publication to IEEE Transactions on Smart Gri
Numerical Bayesian state assignment for a three-level quantum system. I. Absolute-frequency data; constant and Gaussian-like priors
This paper offers examples of concrete numerical applications of Bayesian
quantum-state-assignment methods to a three-level quantum system. The
statistical operator assigned on the evidence of various measurement data and
kinds of prior knowledge is computed partly analytically, partly through
numerical integration (in eight dimensions) on a computer. The measurement data
consist in absolute frequencies of the outcomes of N identical von Neumann
projective measurements performed on N identically prepared three-level
systems. Various small values of N as well as the large-N limit are considered.
Two kinds of prior knowledge are used: one represented by a plausibility
distribution constant in respect of the convex structure of the set of
statistical operators; the other represented by a Gaussian-like distribution
centred on a pure statistical operator, and thus reflecting a situation in
which one has useful prior knowledge about the likely preparation of the
system.
In a companion paper the case of measurement data consisting in average
values, and an additional prior studied by Slater, are considered.Comment: 23 pages, 14 figures. V2: Added an important note concerning
cylindrical algebraic decomposition and thanks to P B Slater, corrected some
typos, added reference
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